Simulation Realism Engineer

About the Team

Our Robotics team is focused on unlocking general-purpose robotics and pushing towards AGI-level intelligence in dynamic, real-world settings. Working across the entire model stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We strive to seamlessly blend high-level AI capabilities with the constraints of physical systems to improve peoples’ lives.

About the Role

We are hiring a Simulation Realism Engineer to drive our effort to make simulation quantitatively real for robotics research and product development. This role owns the strategy, tooling and operational practice that close sim→real gaps across physics, sensors and rendering. You will work cross-functionally with research, software, hardware and ops to discover the highest-impact realism gaps, define measurable realism metrics, and deliver engineering solutions — from tuning engine parameters and asset standards to integrating third-party engines and operating sims at scale. This is a hands-on engineering role that blends scientific rigor (measurement & validation) with pragmatic systems work (tooling, cloud ops, and CI/HIL pipelines).

This role is based in San Francisco, CA. This role will require 4 days in the office per week and offer relocation assistance to new employees.

In this role, you will:

• Define and operationalize realism metrics & protocols. Design experiments and automated tests to find specific areas of non-realism, quantify gaps, and track regressions over time.

• Fine-tune engine parameters (contacts, friction, mass/density, solver settings) and object models so simulated dynamics match measured reality.

• Evaluate, integrate, and — where necessary — extend 3rd-party physics, rendering, and sensor simulation engines (e.g., Isaac, PhysX, MuJoCo, video renderers or sensor sim frameworks). Lead vendor POCs and benchmark features to influence roadmaps.

• Create standards, guidelines, and interactive tools for authoring and validating asset physical/visual properties; implement semi- or fully-automated pipelines to tune and optimize assets for target engines.

• Solve technical issues for running engines in the cloud (OS, drivers, GPU), parallelize simulations (batching many runs per engine instance), and harden real-world-facing pipelines so sims can run reliably at scale.

• Own validation campaigns (teleop, HI